Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
640 detections
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Detects outbound network traffic from browser processes to known BadBlocker extension command-and-control infrastructure (api.adblock-for-youtube.com or get.adblock-for-youtube.com), followed by subsequent outbound HTTPS connections to arbitrary external domains. This sequence is indicative of malicious browser extension activity involving the exfiltration of session cookies or authentication tokens from the victim's browser.
Detects HTTP traffic patterns consistent with data exfiltration to major cloud storage providers (AWS S3, Azure Blob Storage, Google Cloud Storage) using common command-line interface tools like rclone, aws-cli, and AzCopy.
Detects outbound HTTP POST requests where the Content-Length header indicates a data transfer of 5MB or greater. This pattern is indicative of potential unauthorized data exfiltration over the web protocol.
Detects programmatic file downloads from SharePoint and OneDrive using automation tools like PowerShell, PnP, Graph SDK, Python, Node.js, or generic CLI tools (curl, wget) rather than typical browser access. This can indicate data exfiltration.
Detects outbound HTTP POST requests where the Content-Length header indicates a data transfer of 5MB or greater. This pattern is indicative of potential unauthorized data exfiltration over the web protocol.
This rule detects HTTP POST requests containing a Content-Length header value indicating a body size exceeding 10MB. Large POST requests may indicate data exfiltration, large file uploads, or misuse of HTTP channels for data transfer to external destinations.
Detects anomalous activity associated with information stealing malware, including unauthorized access to browser credential files (Login Data, Cookies), remote thread injection into browser processes, outbound connections to the Telegram API by non-browser processes, and rapid bulk access to multiple sensitive credential or crypto wallet files.
This rule monitors for the execution and network activity of known data exfiltration tools such as WinSCP, rclone, and MegaSync. It also tracks the creation of configuration files associated with these tools and monitors DNS requests and browser navigation to known cloud storage and file-sharing destinations. This behavior is indicative of data staging and unauthorized exfiltration.
This rule correlates rapid file modifications (potential encryption or mass deletion) with the execution of commands known to inhibit system recovery (e.g., deleting shadow copies or modifying boot recovery settings) and significant outbound network data transfers from the same host. This pattern is characteristic of ransomware deployment.
Detects outbound network connections to major Large Language Model (LLM) API endpoints (OpenAI, Google, Anthropic) initiated by processes not explicitly identified as standard web browsers or command-line utilities. This pattern may indicate automated data exfiltration ('prompt stealing' or unauthorized access to corporate data) using custom or malicious tools executing from suspicious directories like temp, appdata, or public folders.
Detects anomalous network traffic patterns communicating with the Telegram Bot API (api.telegram.org) from non-official Telegram processes. The rule identifies potential command and control (C2) activity by analyzing request frequency, specific API method usage (e.g., getUpdates, sendMessage), and beaconing-like behavior.
Detects network requests to Google image search containing an 'imgurl' parameter, which can be used by an attacker to exfiltrate data by forcing an external service to crawl a controlled URL containing sensitive information.
This rule detects network connections to Discord's API webhooks endpoint, specifically looking for POST requests. This activity can indicate data exfiltration, command and control communications, or other malicious use of Discord webhooks by adversaries.
Detects rapid high-volume file and messaging operations across multiple Microsoft 365 services (SharePoint, OneDrive, Teams, Exchange) within a compressed 10-minute window from a single identity and IP address. This behavior can indicate data exfiltration or reconnaissance by an adversary.
Detects rapid high-volume file and messaging operations across multiple Microsoft 365 services (SharePoint, OneDrive, Teams, Exchange) within a compressed 10-minute window. This behavior can indicate data exfiltration or collection by an adversary.
Detects DNS resolutions for major AI/LLM provider domains (e.g., OpenAI, Anthropic, Google AI) originating from processes that are not common, known browsers or development tools. This behavior is indicative of potentially malicious applications or malware using AI APIs for automated tasks, such as content exfiltration or sophisticated C2 communication.
Correlates the reading of sensitive local files (id_rsa, .env, config.json) followed by an immediate POST request to an LLM API (specifically api.openai.com), indicating data theft via prompt injection or automated analysis.
Detects activity consistent with the Grandoreiro banking trojan, including DLL sideloading, screen capturing, keystroke hooking, unauthorized network connections to known banking infrastructure, and suspicious data exfiltration bursts.
Detects programmatic file downloads from SharePoint and OneDrive using automation tools like PowerShell, PnP, Graph SDK, Python, Node.js, or generic CLI tools (curl, wget) rather than typical browser access. This can indicate data exfiltration.
Detects browser connections to the Bing Search by Image endpoint, which can be exploited as a Server-Side Request Forgery (SSRF) proxy to bypass Content Security Policies (CSP) and exfiltrate data, as seen in the SearchLeak attack. The rule specifically looks for connections to 'bing.com/images/searchbyimage' that also include the 'imgurl=' or 'imgurl%3d' parameter, indicating an attempt to use Bing's server-side image fetching capability.
Detects outbound network connections to major Large Language Model (LLM) API endpoints (OpenAI, Google, Anthropic) initiated by processes not explicitly identified as standard web browsers or command-line utilities. This pattern may indicate automated data exfiltration ('prompt stealing' or unauthorized access to corporate data) using custom or malicious tools executing from suspicious directories like temp, appdata, or public folders.
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